Proteins fold into their native conformation and undergo a series of post-translational modifications in the endoplasmic reticulum (ER) as part of the normal process of cellular homeostasis. Disruption of any of these processes, for example, accumulation of unfolded or misfolded proteins in the ER, results in ER stress. Cells respond to ER stress by activation of the unfolded protein response (UPR) pathway. Multiple studies support the central role for UPR activation in tumor progression (Bi et al., “ER Stress-regulated Translation Increases Tolerance to Extreme Hypoxia and Promotes Tumor Growth,” EMBO J 24: 3470-81 (2005); Koumenis et al., “Regulation of Protein Synthesis by Hypoxia via Activation of the Endoplasmic Reticulum Kinase PERK and Phosphorylation of the Translation Initiation Factor eIF2α,” Mol Cell Biol 22: 7405-16 (2002); Ameri et al., “Anoxic Induction of ATF-4 Through HIF-1-independent Pathways of Protein Stabilization in Human Cancer Cells,” Blood 103: 1876-82 (2004); Romero-Ramirez et al., “XBP1 is Essential for Survival Under Hypoxic Conditions and is Required for Tumor Growth,” Cancer Res 64: 5943-7 (2004); Shuda et al., “Activation of the ATF6, XBP1 and grp78 Genes in Human Hepatocellular Carcinoma: A Possible Involvement of the ER Stress Pathway in Hepatocarcinogenesis,” J Hepatol 38: 605-14 (2003); Blais et al., “Novel Therapeutic Target: The PERKs of Inhibiting the Integrated Stress Response,” Cell Cycle 5: 2874-7 (2006)). In addition, emerging evidence indicates that prolonged activation of the UPR can be detrimental to neurons and thus mediates neurodegeneration in Alzheimer's disease pathogenesis (Hoozemans et al., “The Unfolded Protein Response is Activated in Alzheimer's Disease,” Acta Neuropathol. 110:165-72 (2005); Hoozemans et al., “The Unfolded Protein Response is Activated in Pretangle Neurons in Alzheimer's Disease Hippocampus,” Am. J Pathol. 174:1241-51 (2009); Unterberger et al., “Endoplasmic Reticulum Stress Features are Prominent in Alzheimer Disease but Not in Prion Diseases In Vivo,” J. Neuropathol. Exp. Neurol. 65:348-57 (2006); Chang et al., “Phosphorylation of Eukaryotic Initiation Factor-2α (eIF2a) is Associated With Neuronal Degeneration in Alzheimer's Disease,” Neuroreport. 13:2429-32 (2002); O'Connor et al., “Phosphorylation of the Translation Initiation Factor eIF2α Increases BACE1 Levels and Promotes Amyloidogenesis,” Neuron 60:988-1009 (2008); Kim et al., “Cell Death and Endoplasmic Reticulum Stress: Disease Relevance and Therapeutic Opportunities,” Nat. Rev. Drug Discov. 7(12):1013-30 (2008)).
PKR-like ER protein kinase (PERK), one of the three identified UPR transducers, is a kinase that phosphorylates a single known substrate eIF2α, leading to lower levels of translation initiation, which in turn globally reduces the load of newly synthesized proteins in the ER (Bi et al., “ER Stress-regulated Translation Increases Tolerance to Extreme Hypoxia and Promotes Tumor Growth,” EMBO J 24:3470-81 (2005); Koumenis et al., “Regulation of Protein Synthesis by Hypoxia via Activation of the Endoplasmic Reticulum Kinase PERK and Phosphorylation of the Translation Initiation Factor eIF2α,” Mol Cell Biol 22: 7405-16 (2002); Shi et al., “Identification and Characterization of Pancreatic Eukaryotic Initiation Factor 2 A-Subunit Kinase, PEK, Involved in Translational Control,” Mol Cell Biol 18:7499-509 (1998); Harding et al., “Regulated Translation Initiation Controls Stress-Induced Gene Expression in Mammalian Cells,” Mol Cell 6:1099-108 (2000)). PERK is a Ser/Thr protein kinase, and its catalytic domain shares substantial homology to other eIF2α family kinases (Harding et al., “Protein Translation and Folding are Coupled by an Endoplasmic-reticulum Resident Kinase,” Nature 397:271-274 (1999)). PERK oligomerization causes its autophosphorylation and kinase domain activation. PERK then phosphorylates and inactivates eIF2α, shutting down mRNA translation and thereby reducing the protein load on the ER (Harding et al., “PERK is Essential for Translational Regulation and Cell Survival During the Unfolded Protein Response,” Mol Cell 5:897-904 (2000)). In addition, PERK-mediated eIF2α phosphorylation also induces the transcriptional activation to improve protein folding capacity, thereby further promoting cell survival (Lu et al., “Translation Reinitiation at Alternative Open Reading Frames Regulates Gene Expression in an Integrated Stress Response,” J Cell Biol 167:27-33 (2004); Wu et al., “From Acute ER Stress to Physiological Roles of the Unfolded Protein Response,” Cell Death Differ 13:374-84 (2006)). Among this group of three prominent UPR transducers which includes XBP1 and ATF6, PERK may have a broader range of cellular effects than other transducers, perhaps due to its role in regulating the general translation rate through the phosphorylation of eIF2α (Blais et al., “Novel Therapeutic Target: The PERKs of Inhibiting the Integrated Stress Response,” Cell Cycle 5:2874-7 (2006)). Indeed, eIF2α phosphorylation appears to account for the entire range of the protective effects of PERK under ER stress (Lu et al., “Cytoprotection by Pre-emptive Conditional Phosphorylation of Translation Initiation Factor 2,” EMBO J 23:169-79 (2004)). Hypoxia, a common feature in solid tumors, results in PERK activation, which protects tumor cells from hypoxic stress (Koumenis et al., “Regulation of Protein Synthesis by Hypoxia via Activation of the Endoplasmic Reticulum Kinase PERK and Phosphorylation of the Translation Initiation Factor eIF2α,” Mol Cell Biol 22:7405-16 (2002); Koritzinsky et al., “Gene Expression During Acute and Prolonged Hypoxia is Regulated by Distinct Mechanisms of Translational Control,” EMBO J 25:1114-25 (2006)).
Drug discovery aimed at a particular molecular target like PERK theoretically has three components: 1) screening to identify lead compounds; 2) preclinical testing of lead compounds, including studies of their effects in animals and 3) clinical testing and approval of the drug.
Combinatorial chemistry is a recent addition to the toolbox of chemists and represents a field of chemistry dealing with the synthesis of a large number of chemical entities for the purposes of screening phase of drug discovery. This is generally achieved by condensing a small number of reagents together in all combinations defined by a given reaction sequence. Advances in this area of chemistry include the use of chemical software tools and advanced computer hardware which has made it possible to consider possibilities for synthesis in orders of magnitude greater than the actual synthesis of the library compounds. The concept of “virtual library” is used to indicate a collection of candidate structures that would theoretically result from a combinatorial synthesis involving reactions of interest and reagents to effect those reactions. It is from this virtual library that relevant compounds are selected to be actually synthesized.
Computer-aided drug design is now widely recognized as a viable alternative and complement to the high-throughput screening (Marrero-Ponce et al., “TOMOCOMD-CARDD, A Novel Approach for Computer-Aided ‘Rational’ Drug Design: I. Theoretical and Experimental Assessment of a Promising Method for Computational Screening and in silico Design of New Anthelmintic Compounds,” J Comput Aided Mol Des 18:615-34 (2004)). Drug discovery has moved toward more rational drug design strategies based on the increasing understanding of the fundamental principles of protein-ligand interactions, leading to many successes and an increased reliance on computational approaches (Chao et al., “Computer-aided Rational Drug Design: A Novel Agent (SR13668) Designed to Mimic the Unique Anticancer Mechanisms of Dietary Indole-3-carbinol to Block Akt Signaling,” J Med Chem 50:3412-5 (2007); Zotchev et al., “Rational Design of Macrolides by Virtual Screening of Combinatorial Libraries Generated Through in silico Manipulation of Polyketide Synthases,” J Med Chem 49:2077-87 (2006); Zauhar et al., “Shape Signatures: A New Approach to Computer-Aided Ligand- and Receptor-based Drug Design,” J Med Chem 46:5674-90 (2003); Grassy et al., “Computer-assisted Rational Design of Immunosuppressive Compounds,” Nat Biotechnol 16:748-52 (1998)).
For example, Project Library (MDL Information Systems, Inc., San Leandro, Calif.) is said to be a desktop software system which supports combinatorial research efforts (A. W. Czaniik and S. H. DeWitt, Practical Guide to Combinatorial Chemistry, ACS, Washington, D.C. (1997)). The software includes an information-management module for the representation and search of building blocks, individual molecules, complete combinatorial libraries, and mixtures 4Q of molecules, and other modules for computational support for tracking mixture and discrete-compound libraries. Similarly, Molecular Diversity Manager (Tripos, Inc., St. Louis, Mo.) is said to be a suite of software modules for the creation, selection, and management of compound libraries (A. W. Czaniik and S. H. DeWitt, Practical Guide to Combinatorial Chemistry, ACS, Washington, D.C. (1997)). The LEGION and SELECTOR modules are said to be useful in creating libraries and characterizing molecules in terms of both 2-dimensional and 3-dimensional structural fingerprints, substituent parameters, topological indices, and physicochemical parameters.
Preclinical evaluation of lead compounds in animals is a critical step for successful drug discovery. For cancer therapeutics, two types of mouse models provide easy and reliable initial preclinical testing of lead compounds: a) a mouse xenograft model, in which foreign (e.g., human) tumors are implanted into immune deficient mice, where they implant and grow and where their response in vivo to lead compounds can be measured; and b) a genetic tumor mouse model, in which the mouse is bred to have a genetic deficiency that results in the development of a tumor at a certain age. The latter is a more predictive model of drug success in humans, but the former afford the capability to test the efficacy of drugs designed to target human proteins inside the mouse. For the unfolded protein response, the Tsc +/−mouse model is an appropriate genetic model (Ozcan U, et al., “Loss of the Tuberous Sclerosis Complex Tumor Suppressors Triggers the Unfolded Protein Response to Regulate Insulin Signaling and Apoptosis,” Mol. Cell; 29:541-551 (2008)) and several standard xenograft models are available (Bi M, et al., “ER Stress-regulated Translation Increases Tolerance to Extreme Hypoxia and Promotes Tumor Growth,” EMBO J; 24:3470-81 (2002)). The SXFAD mouse transgenic model is an appropriate animal model for the preclinical evaluation of lead compounds on their pharmacologic inhibition of Alzheimer's disease progression. Pursuing a model of mouse PERK inhibition first and then translating the findings to human PERK via xenograft models represents a more feasible pathway of preclinical mouse testing of lead compounds.
The present invention is directed to overcoming these and other deficiencies in the art.